| Tao Chen Title: Associate Professor Research directions: Power System Operation, Electricity Market, AI applications Email: taoc@seu.edu.cn Office phone: 15706152678 |
Biography：
I am currently an Associate Professor in School of Electrical Engineering, Southeast University, China. My research interests are about power system operation, electricity market and AI applications. Before joining in Southeast University, I worked as a Postdoctoral Associate with Prof. Saifur Rahman in Advanced Research Institute (ARI), Virginia Tech, Washington D.C., USA, 2018-2019. I also worked as an Intern Engineer in Global Energy Interconnection Research Institute North America (GEIRINA), California, USA, 2017-2018 and Project Researcher in Tampere University of Technology, Finland, 2013-2015. I received my MSc and PhD from Tampere University of Technology, Finland, 2012-2015 and University of Michigan, USA, 2015-2018, respectively, all in Electrical Engineering. I have (co)authored more than 100 publications and PI for 20+ R&D projects, including Portugal NESTER Joint Project, National Natural Science Foundation of China (NSFC), and State Grid Corporation of China (SGCC).
Publications：
Zhang, Chao, Yunfeng Ma, Guolin Yang, andT. Chen. "An integrated industrial PV panel cleaning recommendation system for optimal dust removal." Applied Energy 377 (2025): 124692.
Wang, Sheng, Hongxun Hui,T. Chen, and Junyi Zhai. "Multi-period operation of integrated electricity and gas systems with hydrogen blending considering gas composition dynamics." Applied Energy 377 (2025): 124563.
Xu, Tianyun,T. Chen, Ciwei Gao, Meng Song, Yishen Wang, and Hao Yuan. "Distributed flexible resource regulation strategy for residential communities based on deep reinforcement learning." IET Generation, Transmission & Distribution (2024).
T. Chen and C. Gao, “Intelligent Electric Vehicle Charging Scheduling in Transportation-energy Nexus with Distributional Reinforcement Learning”, IEEE/CAA Journal of Automatica Sinica, vol. 10, no. 11, pp. 2171-2173, 2023.
T. Xu,T. Chen, C. Gao and H. Hui, "Intelligent Home Energy Management Strategy With Internal Pricing Mechanism Based on Multiagent Artificial Intelligence-of-Things," in IEEE Systems Journal, vol. 17, no. 4, pp. 6045-6056, Dec. 2023.
T. Chen, C. Gao, and Y. Song, “Optimal control strategy for solid oxide fuel cell‐based hybrid energy system using deep reinforcement learning”,IET Renewable Power Generation, vol.16, no.5, pp.912-921, 2022.
T. Chen, Q. Cui, C. Gao, and et. al., “Optimal Demand Response Strategy of Commercial Building-based Virtual Power Plant using Reinforcement Learning”,IET Generation, Transmission & Distribution, April 2021.
T. Chen, M. Pipattanasomporn, I. Rahman, Z. Jing, and S. Rahman, “MATPLAN: A Probability-based Planning Tool for Cost-effective Integration of Renewable Energy into the Electricity Grid”,Renewable Energy, vol.156, pp.1089-1099, August 2020.
T. Chen, and W. Su, "Indirect Customer-to-Customer Energy Trading with Reinforcement Learning",IEEE Trans. on Smart Grid, vol.10, no. 4, pp.4338-4348, 2019.
T. Chen, B. Zhang, H. Pourbabak, A. K. Fard, and W. Su, “Optimal Routing and Charging of an Electric Vehicle Fleet for High-Efficient Dynamic Transit Systems”,IEEE Trans. on Smart Grid, vol.9, no.4, pp.3563-3572, July 2018.
X. Zhang, M. Pipattanasomporn,T. Chen, and S. Rahman, "An IoT-based Thermal Model Learning Framework for Smart Buildings",IEEE Internet of Things Journal, 2019, vol.7, no.1, pp.518 – 527, 2019.
H. Hui, Y. Ding,T. Chen, S. Rahman, and Y. Song, “Dynamic and Stability Analysis of the Power System With the Control Loop of Inverter Air Conditioners”, IEEE Transactions on Industrial Electronics, 2020.
H. Pourbabak, J. Luo,T. Chen, and W. Su, "A Novel Consensus-based Distributed Algorithm for Economic Dispatch Based on Local Estimation of Power Mismatch", IEEE Trans. on Smart Grid, vol.9, no.6, pp.5930-5942, November 2018.
K.Lai,T. Chen, and B. Natarajan, “Optimal scheduling of electric vehicles car-sharing service with multi-temporal and multi-task operation”, Energy, vol.204, 2020.
D. Li, C. Gao,T. Chen, X. Guo, and S. Han. "Planning strategies of power-to-gas based on cooperative game and symbiosis cooperation."Applied Energy 288 (2021): 116639.
Y. Yao, C. Gao,T. Chen, J. Yang, and S. Chen, “Distributed electric energy trading model and strategy analysis based on prospect theory”, International Journal of Electrical Power & Energy Systems, vol. 131, 2021.
Y. Yao, C. Gao, K. Lai,T. Chen, and J. Yang, “An incentive-compatible distributed integrated energy market mechanism design with adaptive robust approach”, Applied Energy, vol.282, 2021.
Y. Xu, K. Mert, L. Mili, J. Valinejad,T. Chen, and X. Chen, "An Iterative Response-Surface-Based Approach for Chance-Constrained AC Optimal Power Flow Considering Dependent Uncertainty",IEEE Transactions on Smart Grid,2021.
M. Niu, C. Gao, andT. Chen. “Energy Pricing Mechanism Considering Energy Converter Devices as Components of Pan-Energy Transmission System”,IEEE Transactions on Smart Grid, 2021.
Li, T., Gao, C.,T. Chen, Jiang, Y., & Feng, Y. “Medium and long-term electricity market trading strategy considering renewable portfolio standard in the transitional period of electricity market reform in Jiangsu, China”, Energy Economics, 105860, 2022.
Yan, X., Gao, C., Song, M.,T. Chen, Ding, J., Guo, M., ... & Abbes, D. An IGDT-based Day-ahead Co-optimization of Energy and Reserve in a VPP Considering Multiple Uncertainties. IEEE Transactions on Industry Applications, 2022.
H Hui, Y Ding, K Luan,T Chen, Y Song, S Rahman, “Coupon-Based Demand Response for Consumers Facing Flat-Rate Retail Pricing”, CSEE Journal of Power and Energy Systems, 2022.
Research：
Research on Key Technologies of Distributed Flexible Resource Aggregation and Optimization for EU Market Operation (January 2023 – December 2024), 6,500,000 CNY
Intelligent decision-making in Transactive Energy System based on Deep Reinforcement learning and Internet-of-things (January 2022 – December 2024), 240,000 CNY
Large-scale Demand Side Resources Operation for Power System Planning and Management (January 2021 – December 2022), 2,200,000 CNY
Efficiency Analysis and Policy Recommendation of Jiangsu Power Market Design and Operation (June 2020 – November 2021), 250,000 GBP
Teaching：
Power System Planning (Graduate, 32 course hours, Southeast University - Monash University Joint Graduate School (Suzhou))
Power Plant and Electric Facilities (Undergraduate, 32 course hours)
AI Applications in Power System (Graduate, 32 course hours)
Fundamentals of Power System Economics (Graduate, 32 course hours)
